huberloss.md
huberloss
R Documentation
Huber Loss
Description
A generic S3 function to compute the huber loss score for a regression
model. This function dispatches to S3 methods in huberloss() and
performs no input validation. If you supply NA values or vectors of
unequal length (e.g. length(x) != length(y)), the underlying C++
code may trigger undefined behavior and crash your R session.
Defensive measures
Because huberloss() operates on raw pointers, pointer-level faults
(e.g. from NA or mismatched length) occur before any R-level error
handling. Wrapping calls in try() or tryCatch() will not preventR-session crashes.
To guard against this, wrap huberloss() in a "safe" validator that
checks for NA values and matching length, for example:
safe_huberloss <- function(x, y, ...) {
stopifnot(
!anyNA(x), !anyNA(y),
length(x) == length(y)
)
huberloss(x, y, ...)
}Apply the same pattern to any custom metric functions to ensure input
sanity before calling the underlying C++ code.
Usage
## Generic S3 method
## for Huber Loss
huberloss(...)
## Generic S3 method
## for weighted Huber Loss
weighted.huberloss(...)Arguments
...
Arguments passed on to huberloss.numeric,weighted.huberloss.numeric
actual,predicted
A pair of <double> vectors of length n.
delta
A <double>-vector of length 1
(default: 1). The threshold value for switch
between functions (see calculation).
w
A <double> vector of sample weights.
Value
A <double> value
References
James, Gareth, et al. An introduction to statistical learning. Vol. 112. No. 1. New York: springer, 2013.
Hastie, Trevor. "The elements of statistical learning: data mining, inference, and prediction." (2009).
Virtanen, Pauli, et al. "SciPy 1.0: fundamental algorithms for scientific computing in Python." Nature methods 17.3 (2020): 261-272.
Examples
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